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Language: English

Conflict of Interest: In relation to this article, we declare that there is no conflict of interest.

Publication history: Received February 24, 2009
Accepted August 19, 2009

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Settling state detection of SBR based on DO profile analysis using dynamic time warping

Yejin Kim^† Hyeon Bae¹ Hyosoo Kim Jungphil Shin² Changwon Kim

Department of Environmental Engineering, Pusan National University, Busan, Korea ¹Busan Techno-Park, Busan, Korea ²Aizu International University, Japan

Korean Journal of Chemical Engineering, February 2010, 27(2), 504-510(7), 10.1007/s11814-010-0081-2

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Abstract

Settleability of activated sludge is one of the most important variables for stable solid-liquid separation of the biological wastewater process. Moreover, effective decanting is a sensitive work at sequencing batch reactor (SBR) which has a settleability fault, such as filamentous/non-filamentous bulking, deflocculation and sludge rising. It is not easy to monitor sludge settleability directly without any specified measurement system, but the values of settling phase can be measured by installing basic measuring instruments for monitoring the process in the reaction stage of SBR. In this study, patterns of DO profiles measured at settling phase showing significant difference according to the process status were used to explore whether a problem occurs or not. To use this information, an online algorithm was developed to detect and diagnose the settling fault. A dynamic programming method that is one of the pattern recognition methods was used to detect and classify the patterns of the DO profiles. Based on the discriminant function made by dynamic time warping results and an extracted variable from DO profiles, the classification rules were generated. With the discriminant function, the settleability fault was detected and classified successfully.

Keywords

Detection Diagnosis Discriminant Analysis DO Dynamic Time Warping SBR Settleability

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